A lot of the Mackay book is on information/coding theory and while it will deepen an existing understanding of ML, its probably a roundabout introduction. ESL is a much better intro, especially for someone looking to apply ML.
That said, it is meant for people who are comfortable with math/stats; its much more statistics oriented than, say, Mitchell's book. But they do a good job of explaining things in non-math language. This book does a good job of exposing high level ML concepts (e.g. bias-variance tradeoff) but still teaches a lot of the standard methods & tools.
These are actually two of my favorite books on the subject and I can't recommend them both enough.
That said, it is meant for people who are comfortable with math/stats; its much more statistics oriented than, say, Mitchell's book. But they do a good job of explaining things in non-math language. This book does a good job of exposing high level ML concepts (e.g. bias-variance tradeoff) but still teaches a lot of the standard methods & tools.
These are actually two of my favorite books on the subject and I can't recommend them both enough.